Project Team:

Nathan Alexander (Howard University)

Anika Hobson (Nubian Hueman)

Zoe Williams (Howard University)

Qyana Stewart (Howard University)

OVERVIEW

Whatever happened to Chocolate City, the term used to refer to Washington DC’s Black population?

In this short report, we discuss some key historical and contemporary connections and then we analyze US census data to examine historical and continual shifts in Washington DC’s Black population. We focus on racial isolation and residential segregation. We close with a discussion on how modern critical theories, mathematics, and population-level data can increase our general knowledge as a community and inform our perspectives on local policies and social action issues, like voting and community service.

The materials presented here are for the October 2024 workshop at Nubian Hueman studios in DC.

BACKGROUND

The phrase “Chocolate City” has long been used to describe Washington, D.C.’s significant Black population and vibrant Black communities. However, in recent decades, the appropriateness of this label has come into question due to shifting demographics and changing urban dynamics.

Washington, D.C. reached its peak as a majority-Black city in 1970, when African Americans comprised 71% of the population. Since then, the city has experienced a steady decline in its Black population. By 2015, DC’s population of Black residents had decreased to 48% and the current population is 44%.

Factors contributing to the changes

Several factors have contributed to the erosion of D.C.’s status as a “Chocolate City”:

  • Gentrification: Rising property values and cost of living have pushed many long-time Black residents out of traditionally African American neighborhoods

  • Suburban migration: Many middle-class Black families have moved to more affordable suburbs in Maryland and Virginia

  • Urban redevelopment: The replacement of public housing projects with mixed-income developments has altered the demographic makeup of some areas

Segregation

Despite increasing diversity, Washington, D.C. remains highly segregated. The Black-White segregation index stood at 70 in 2015, showing only modest improvement from 77 in 1980. This suggests that while the overall racial composition of the city has changed, residential patterns of segregation persist, often isolating poor Black residents.

Cultural significance

The “Chocolate City” moniker continues to hold cultural significance, even as its demographic accuracy wanes. It represented not just a statistical majority, but also the city’s important role in Black history, culture, and political aspirations. As Washington, D.C. evolves, the question remains whether the “Chocolate City” label will continue to resonate or if new descriptors will emerge to capture the city’s changing identity.

Implications

As of 2022, the racial composition of Washington, D.C. has changed considerably:

Black or African American (Non-Hispanic): 43.5%
White (Non-Hispanic): 36.3%
Hispanic (of any race): 4.05%
Asian (Non-Hispanic): 3.95%
Two or more races (Non-Hispanic): 3.94%

This shift represents a significant change from the city’s historical Black majority.

In this workshop, we examine the various quantitative and historical factors that have contributed race and isolation in DC.

DATA

The discussions and analysis in this report are informed by the US Census microdata, which was accessed through the tidycensus() package in R. The American Community Survey (ACS) Public Use Microdata Sample (PUMS) is used to analyze pre-aggregate data at a local level. This data allowed us to make various custom estimates that may not be normally available by the US Census Bureau.

Learn more about PUMS here.

In our data, “totalpopE” is a single number representing the estimated population, while “totalpopM” represents a range around that estimate within which the true population is likely to fall. The designation for “E” and “M” follows in line as the estimate and the margin of error.

## Getting data from the 2016-2020 5-year ACS
## Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

## Getting data from the 2016-2020 5-year ACS
## Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

## Getting data from the 2016-2020 5-year ACS
## Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## [1] 0.10294295 0.10851649 0.08528862 0.07015620 0.05529833 0.18958024

## Simple feature collection with 206 features and 28 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -77.11976 ymin: 38.79165 xmax: -76.9094 ymax: 38.99511
## Geodetic CRS:  NAD83
## # A tibble: 206 × 29
##    GEOID.x   totalpopE pwhite pblack pasian phisp whiteE blackE asianE hispanicE
##    <chr>         <dbl>  <dbl>  <dbl>  <dbl> <dbl>  <dbl>  <dbl>  <dbl>     <dbl>
##  1 11001001…      3489  67.3    6.05  8.08  12.6    2348    211    282       441
##  2 11001002…      4104  33.4   25.4   7.94  28.6    1371   1041    326      1175
##  3 11001003…      3825  41.8   25.8   3.22  24.1    1598    987    123       921
##  4 11001004…      4785  82.2    4.76  2.70   7.57   3932    228    129       362
##  5 11001010…      3927  54.6   28.8   3.54   8.71   2143   1130    139       342
##  6 11001004…      3169  42.1   43.7   4.64   5.93   1335   1384    147       188
##  7 11001008…      3376  21.6   59.1   1.66  14.0     730   1996     56       472
##  8 11001009…      1889   3.55  79.0   0.212 15.7      67   1493      4       296
##  9 11001009…      3575   8.87  80.9   0      7.55    317   2893      0       270
## 10 11001005…      2723  72.8    3.12 14.1    8.52   1981     85    384       232
## # ℹ 196 more rows
## # ℹ 19 more variables: incomeE <dbl>, STATEFP <chr>, PLACEFP <chr>,
## #   PLACENS <chr>, AFFGEOID <chr>, GEOID.y <chr>, NAME <chr>, NAMELSAD <chr>,
## #   STUSPS <chr>, STATE_NAME <chr>, LSAD <chr>, ALAND <dbl>, AWATER <dbl>,
## #   geometry <POLYGON [°]>, white.tot <dbl>, asian.tot <dbl>, black.tot <dbl>,
## #   hisp.tot <dbl>, tpopc <dbl>
## Getting data from the 2016-2020 5-year ACS
## Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
## [1] 0.04797083 0.04003167 0.03181145 0.02965383 0.01987875 0.17114119
## New names:
## • `` -> `...1`
## • `` -> `...2`
## # A tibble: 6 × 2
##    Black Hispanic
##    <dbl>    <dbl>
## 1 0.103    0.0480
## 2 0.109    0.0400
## 3 0.0853   0.0318
## 4 0.0702   0.0297
## 5 0.0553   0.0199
## 6 0.190    0.171

Map: Washington, DC